Comparative Experimental Evaluation Research Articles

Comprehensive evaluation of solar floating photovoltaic prospective in Saudi Arabia: Comparative experimental investigation and thermal performance analysis

Recently, floating photovoltaic systems have been regarded as a promising technology for producing clean energy by utilizing the surface of water bodies, such as lakes, rivers and oceans. This study introduces a comparative experimental study and energy performance evaluation of a 1.0 kW offshore floating photovoltaic (FPV) system and a nearby traditional ground-based PV system (GPV) installed in the eastern province of Saudi Arabia. The FPV system was deployed in the Arabian Gulf, 25 m off the coast, at an average depth of 1 to 1.5 m depending on tide, wave, and current intensity. The FPV system employs a strong novel eco-friendly platform structure made of recycled buoyant materials such as engineered plastic drums and wood. This system is anchored with tension cables and concrete blocks that can withstand the changing sea water conditions. The GPV system, on the other hand, was installed 150 m inland from the shore. Real-time monthly data monitoring and assessment indicated that FPV systems outperformed GPV systems in terms of lower PV panel surface temperatures, higher power output, and panel efficiency. Based on daily average back surface temperatures, FPV system temperature was decreased by 7.5 % to 21.34 % when compared to GPV. Moreover, the FPV system efficiency was also increased by 12.2 % when compared to the GPV system. This study aims to assist in promoting the applicability of solar floating photovoltaic systems to synergistically fulfill the requirements of sustainable electricity production for the arid costal community in Saudi Arabia and similar areas.

Comparative Experimental Evaluation of Orthodontic Appliances for Maxillary Arch Expansion

Background/Objectives: The orthodontic treatment of posterior crossbite using appliances for gradual maxillary expansion is crucial to ensure proper transversal jaw relationships as much as occlusal functionality. The aim of this study was to analyze forces and torques generated by different appliances for maxillary expansion. Methods: Measurements were conducted for the Wilson® 3D® Quadhelix (WQH) and Wilson® 3D® Multi-Action Palatal Appliance (WPA) across various sizes and compared to the Remanium® Quadhelix (RQH). Activations were set to 8 mm for the WQH and RQH and 6 and 8 mm for the WPA. Rotations and root torque were simulated via an activation of 10° for arches. A total of eight test series were conducted. Results: The WPA displayed the highest force and torque values for all movements, far surpassing recommended guideline values (expansion 8.5–>15.0 N/46.3–86.5 Nmm, rotation 3.1–6.1 N/40.7–61.4 Nmm, torque 3.9–5.1 N/22.4–29.7 Nmm), and the WQH displayed the lowest values (expansion 2.7–12.6 N/11.1–39.6 Nmm, rotation 0.1–1.7 N/23.0–32.2 Nmm, torque 0.9–2.9 N/3.4–10.5 Nmm). Appliances with the smallest transverse dimensions exhibited the highest force and torque maxima. Conclusions: This study underscores the importance of understanding biomechanical principles in orthodontics for minimizing unintended tooth movements, providing detailed insights into the force systems of appliances acting in the transverse plane, and establishing a foundation for future clinical investigations to validate these in vitro findings.

Learning the Ego-Motion of an Underwater Imaging Sonar: A Comparative Experimental Evaluation of Novel CNN and RCNN Approaches

Learning the Ego-Motion of an Underwater Imaging Sonar: A Comparative Experimental Evaluation of Novel CNN and RCNN Approaches

Graph Convolutional Recommendation System Based on Bilateral Attention Mechanism

Collaborative Filtering Recommender Systems face data sparsity and cold‐start issues, leading to a decrease in their recommendation performance. Therefore, numerous researchers have integrated knowledge graphs and graph convolutional networks into recommender systems to enhance their performance. Through an analysis of previous knowledge graph convolutional network recommendation systems, the following problems have been identified: (1) Some graph convolutional networks only consider the neighborhood aggregation of items while neglecting the neighborhood aggregation of users. (2) User rating differences are not taken into account. To tackle these problems, a Bilateral Attention Mechanism Graph Convolutional Network Recommender Model is proposed. This model effectively captures high‐order neighborhood information for both items and users by utilizing bipartite attention mechanisms on the knowledge graph and interaction graph. Additionally, it incorporates the influence of user ratings on items. Finally, it aggregates item and user information with neighborhood information to predict user ratings for items. The validity of this model was verified through experimental analysis and comparative evaluation of its performance against SPGCN, CACF on the MovieLens‐20M, Book‐Crossing, and Last.FM datasets.

Experimental Analysis of Large-Scale Learnable Vector Storage Compression

Learnable embedding vector is one of the most important applications in machine learning, and is widely used in various database-related domains. However, the high dimensionality of sparse data in recommendation tasks and the huge volume of corpus in retrieval-related tasks lead to a large memory consumption of the embedding table, which poses a great challenge to the training and deployment of models. Recent research has proposed various methods to compress the embeddings at the cost of a slight decrease in model quality or the introduction of other overheads. Nevertheless, the relative performance of these methods remains unclear. Existing experimental comparisons only cover a subset of these methods and focus on limited metrics. In this paper, we perform a comprehensive comparative analysis and experimental evaluation of embedding compression. We introduce a new taxonomy that categorizes these techniques based on their characteristics and methodologies, and further develop a modular benchmarking framework that integrates 14 representative methods. Under a uniform test environment, our benchmark fairly evaluates each approach, presents their strengths and weaknesses under different memory budgets, and recommends the best method based on the use case. In addition to providing useful guidelines, our study also uncovers the limitations of current methods and suggests potential directions for future research.

Research on the influence of stress wave on crack and chip formation mechanism in radial ultrasonic vibration assisted grinding

The propagation of stress waves in the ultrasonic vibration grinding zone was studied and analyzed in this paper and the microscopic mechanism of ultrasonic vibration assisted grinding is clarified by combining the method of finite element analysis (FEA). The creation of an experimental platform for ultrasonic vibration assisted grinding allowed for a comparative experimental evaluation of radial ultrasonic vibration assisted grinding (RUVAG) and conventional grinding (CG). Experiments analysis show that: (a) Compared with conventional grinding, the alternating impact of stress waves in ultrasonic vibration grinding is beneficial to the propagation of microcracks and the removal of materials. Meanwhile, there is no burn on the machined surface, so the quality of the machined surface is better. (b) Under the alternating and superimposed action of stress waves, dislocation emission becomes difficult due to the suppressed thermal activation process. Therefore, the plastic deformation of the material is suppressed and reduced in the grinding zone, and the material is more likely to break than during conventional grinding. Therefore, compared with conventional grinding, both cracks and chips are easier to form in it..

A comparative experimental performance evaluation of solar air collector having absorber plate with convex oval-trench dimple

A comparative experimental performance evaluation of solar air collector having absorber plate with convex oval-trench dimple

Ultra-Low Losses SiC-Based Active Damper for Industrial Power Systems: Mitigating Harmonic Distortion and Maximizing Harmonic Power Recovery

Wideband harmonics and undamped resonances have become problems of major concern for industrial end-users in the last time. Although passive dampers are the simplest solution to combat the mentioned problems, passive dampers convert the harmonic active power ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$P_{H}$</tex-math></inline-formula> ) they absorb to heat, leading to energy waste. Conversely, active dampers not only reduce harmonic distortion and suppress resonances but can also perform harmonic power recovery. In effect, harmonic power recovery implies transforming the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$P_{H}$</tex-math></inline-formula> absorbed into fundamental active power that is injected back into the power system. This paper introduces a mathematical model that describes the mechanisms and necessary conditions of harmonic power recovery within an active damper. The model shows that a substantial amount of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$P_{H}$</tex-math></inline-formula> can be recovered only if the active damper's power losses are significantly smaller than the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$P_{H}$</tex-math></inline-formula> absorbed. Consequently, this paper presents the implementation of an ultra-low losses 82 kVA active damper based on SiC MOSFETs which recovers around 80% of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$P_{H}$</tex-math></inline-formula> absorbed. Moreover, a comparative experimental evaluation was carried out between the proposed active damper and an IGBT-based active damper. The comparison shows that the amount of harmonic power recovered can be increased by a factor of four using the SiC-based active damper.

Distinguishing nanoparticle drug release mechanisms by asymmetric flow field-flow fractionation.

This research demonstrates the development, application, and mechanistic value of a multi-detector asymmetric flow field-flow fractionation (AF4) approach to acquire size-resolved drug loading and release profiles from polymeric nanoparticles (NPs). AF4 was hyphenated with multiple online detectors, including dynamic and multi-angle light scattering for NP size and shape factor analysis, fluorescence for drug detection, and total organic carbon (TOC) to quantify the NPs and dissolved polymer in nanoformulations. The method was demonstrated on poly(lactic-co-glycolic acid) (PLGA) NPs loaded with coumarin 6 (C6) as a lipophilic drug surrogate. The bulk C6 release profile using AF4 was validated against conventional analysis of drug extracted from the NPs and complemented with high performance liquid chromatography - quadrupole time-of-flight (HPLC-QTOF) mass spectrometry analysis of oligomeric PLGA species. Interpretation of the bulk drug release profile was ambiguous, with several release models yielding reasonable fits. In contrast, the size-resolved release profiles from AF4 provided critical information to confidently establish the release mechanism. Specifically, the C6-loaded NPs exhibited size-independent release rate constants and no significant NP size or shape transformations, suggesting surface desorption rather than diffusion through the PLGA matrix or erosion. This conclusion was supported through comparative experimental evaluation of PLGA NPs carrying a fully entrapped drug, enrofloxacin, which showed size-dependent diffusive release, along with density functional theory (DFT) calculations indicating a higher adsorption affinity of C6 onto PLGA. In summary, the development of the size-resolved AF4 method and data analysis framework fulfills salient analytical gaps to determine drug localization and release mechanisms from nanomedicines.

Comparative Experimental Evaluation of L-carnitine and Cholecalciferol on Amikacin Induced Nephrotoxicity and Clinical Evaluation of Amikacin Induced Adverse Drug Reactions

Background: Reduction of health cost burden with existing low-cost drug and thereby improving patient compliance is utmost necessary. Keeping in mind the above, we started with low cost, broad spectrum, WHO enlisted essential drug amikacin. We tried to revaluate it with another two low-cost drugs, L-carnitine, and Cholecalciferol. Objectives: Measurement of amikacin induced nephrotoxicity by means of abnormal renal biochemical parameters on albino rats and comparison of improvement after administration of L-carnitine &amp; Cholecalciferol along with renal histopathology examination (HPE) of amikacin treated rats and causality assessment of amikacin induced adverse drug reactions (ADR) in hospitalized patient. Materials and Methods: Healthy albino male rats (N=40) were taken from Institutional animal house of Burdwan medical College and Hospital (BMCH) and were randomly divided into 4 groups. CPCSEA acclimatization guideline followed. IEAC and CREC clearances taken. Renal biochemical parameters from blood samples were analysed. Sterile water for injection was given to all group. Group I is control (only vehicle), Amikacin added to Group II, III and IV. L carnitine &amp; Cholecalciferol was added to Group III &amp; Group IV respectively. Post test measurement of renal biochemical parameters and HPE were done. Clinical observation of amikacin treated hospitalised patients and collection of their ADR in BMCH were done to find out correlations with animal experiment. Results: Statistical analyses were done using Graph Pad Prism version.4 software. Minimisation of amikacin induced nephropathy were seen, more in Group IV than Group III. HPE found the same conclusion. WHO UMC causality assessment revealed, 94.35% ADR were “probable/likely” whereas 5.65% were “possible”. The Naranjo’s adverse reaction probability scale revealed almost the same. Conclusion: Interventional animal experiment, biochemical parameters, histopathology along with open label, non-interventional, prospective observational study clearly indicates cholecalciferol is significantly better than L carnitine to minimise the effects of amikacin induced nephropathy.

Multi-density urban hotspots detection in smart cities: A data-driven approach and experiments

The detection of city hotspots from geo-referenced urban data is a valuable knowledge support for planners, scientists, and policymakers. However, the application of classic density-based clustering algorithms on multi-density data can produce inaccurate results. Since metropolitan cities are heavily characterized by variable densities, multi-density clustering seems to be more appropriate to discover city hotspots. This paper presents CHD (City Hotspot Detector), a multi-density approach to discover urban hotspots in a city, by reporting an extensive comparative analysis with three classic density-based clustering algorithms, on both state-of-the-art and real-world datasets. The comparative experimental evaluation in an urban scenario shows that the proposed multi-density algorithm, enhanced by an additional rolling moving average technique, detects higher quality city hotspots than other classic density-based approaches proposed in literature.

Comparative experimental evaluation and thermodynamic analysis of the possibility of using degraded C15-C50 crankcase oil waste as thermal storage materials in solar drying systems

The study presents a comparative thermodynamic analysis of degraded C15-C50 grade crankcase oil (DCO) and paraffin thermal storage (PTS) as heat storage materials in solar drying. The goal is to convert DCO from waste to a useful product in solar drying. The assessment was based on drying efficiency, energy and exergy analysis, sustainability assessment and CO2 mitigation of each solar dryer. The difference in drying efficiency between the dryer with DCO and that with PTS is less than 1.5 % while the difference between the specific energy consumption is less than 9 %. In contrast, the difference between the dryer with DCO and that without thermal storage is 24.2 %. The mean exergy efficiency ranged between 41.6 and 49.9 %. The values of the waste exergy ratio (WER), sustainability index (SI) and improvement potential (IP) for the three dryers ranged from 0.00 ≤ WER ≤ 1.00, 0.00 ≤ SI ≤ 34.56, 0.00 ≤ IP ≤ 2.68 kW. Using these dryers instead of diesel, grid-based electricity or coal-powered dryer will limit a maximum of 5,792,826 tons of CO2 from the atmosphere.

A comparative experimental evaluation of various Smith predictor approaches for a thermal process with large dead time

This paper emphasizes a comparative experimental evaluation of three Smith predictor configurations. The three control schemes are tuned using different optimization algorithms; then, they are applied to an Arduino Temperature Control Lab used to test and evaluate their performance. The three deadtime compensators are compared using radial graphs. They were assessed under different conditions using various performance indices: the Integral Square Error, the Total Variations of Control Efforts, the Maximum Overshoot, and the Settling Time for tracking and disturbances changes. The Mejia et al. approach presented a better overall performance than the other two. Finally, the results showed that Smith Predictor is suitable for thermal processes with elevated dead time.

Coverage and Energy-Efficiency Experimental Test Performance for a Comparative Evaluation of Unlicensed LPWAN: LoRaWAN and SigFox

Low Power Wide Area Networks (LPWAN) have emerged as an appealing IoT communication solution. Large coverage and low power consumption are critical requirements when deploying a communication network to support an IoT application. Despite the fact that existing LPWAN technology solutions promote IoT requirements such as long communication range, energy efficiency, scalability, and low cost, there are numerous concerns about the performance of this type of communication network. With a wide range of LPWAN technologies available, there is growing interest in their evaluation. This paper proposes an experimental comparative evaluation based on coverage and energy-efficiency test performance for LoRaWAN and SigFox, two emerging LPWAN technologies operating in sub-GHz Industrial, Scientific, and Medical (ISM) frequency bands. Recent works have presented various comparison studies of LPWAN technologies, however most of them have been tackled from the perspective of comparing their technical specifications without presenting measurement results obtained from network deployment scenarios. We argue that by proposing a comparative evaluation from an experimental perspective, the comparison discussion is taken to the next level. The experimental evaluation has been proposed first by selecting coverage and energy-efficiency as the most significant design goals for LPWAN applications. Second, by proposing the test performance to evaluate those goals, where extensive measurements are made in network deployments, and finally, by highlighting the main findings about performance for both network for comparison purposes. Results show that in a test with fair conditions LoRaWAN performed better than SigFox in an urban environment in terms of coverage, obtaining a better packet delivery rate (PDR ≳ 80%) with higher radio strength signal (RSSI ≳ - 110 dBm). Whereas Sigfox shows better energy efficiency with a 20 % of more sent messages under the same test conditions.

Magnetic Resonance Imaging of the Knee in the Presence of Bridging External Fixation: A Comparative Experimental Evaluation of Four External Fixators, Including Dolphix®.

Performing MR investigation on patients instrumented with external fixators is still controversial. The aim of this study is to evaluate the quality of MR imaging of the knee structures in the presence of bridging external fixators. Different cadaveric lower limbs were instrumented with the MR-conditional external fixators Hofmann III (Stryker, Kalamazoo, MI, USA), Large external Fixator (DePuy Synthes, Raynham, MA, USA), XtraFix (Zymmer, Warsaw, IN, USA) and a newer implant of Ketron Peek CA30 and ERGAL 7075 pins, Dolphix®, (Citieffe, Bologna, Italy). The specimens were MR scanned before and after the instrumentation. The images were subjectively judged by a pool of blinded radiologists and then quantitatively evaluated calculating signal intensity, signal to noise and contrast to noise in the five regions of interest. The area of distortion due to the presence of metallic pins was calculated. All the images were considered equally useful for diagnosis with no differences between devices (p > 0.05). Only few differences in the quantification of images have been detected between groups while the presence of metallic components was the main limit of the procedure. The mean length of the radius of the area of distortion of the pins were 53.17 ± 8.19 mm, 45.07 ± 4.33 mm, 17 ± 5.4 mm and 37.12 ± 10.17 mm per pins provided by Zimmer, Synthes, Citieffe and Stryker, respectively (p = 0.041). The implant of Ketron Peek CA30 and ERGAL 7075 pins showed the smallest distortion area.

Edge trimming of flax fibers and glass fibers reinforced polymers composite – An experimental comparative evaluation

Edge trimming of flax fibers and glass fibers reinforced polymers composite – An experimental comparative evaluation

A comprehensive survey and experimental comparison of graph-based approximate nearest neighbor search

Approximate nearest neighbor search (ANNS) constitutes an important operation in a multitude of applications, including recommendation systems, information retrieval, and pattern recognition. In the past decade, graph-based ANNS algorithms have been the leading paradigm in this domain, with dozens of graph-based ANNS algorithms proposed. Such algorithms aim to provide effective, efficient solutions for retrieving the nearest neighbors for a given query. Nevertheless, these efforts focus on developing and optimizing algorithms with different approaches, so there is a real need for a comprehensive survey about the approaches' relative performance, strengths, and pitfalls. Thus here we provide a thorough comparative analysis and experimental evaluation of 13 representative graph-based ANNS algorithms via a new taxonomy and fine-grained pipeline. We compared each algorithm in a uniform test environment on eight real-world datasets and 12 synthetic datasets with varying sizes and characteristics. Our study yields novel discoveries, offerings several useful principles to improve algorithms, thus designing an optimized method that outperforms the state-of-the-art algorithms. This effort also helped us pinpoint algorithms' working portions, along with rule-of-thumb recommendations about promising research directions and suitable algorithms for practitioners in different fields.

Experimental Investigation and Comparative Geometrical Evaluation of WCEDM Process on OHNS by using Various Wires

Experimental Investigation and Comparative Geometrical Evaluation of WCEDM Process on OHNS by using Various Wires

A comparative experimental evaluation on performance of type-1 and interval type-2 Takagi-Sugeno fuzzy models

In the literature, there have been numerous studies demonstrating experimentally that type-2 fuzzy models outperform their type-1 counterparts. Although the advantages of these models seem to be well justified, the quantification of the improvements is not carefully evaluated and critically assessed in the existing studies. A thorough multi-objective experimental numeric evaluation of benefits of type-2 fuzzy models is still lacking. In this study, a numeric evaluation of the performance of type-1 and type-2 fuzzy models is carried out in terms of the criteria of accuracy and computing overhead, which leads to a thorough analysis of existing trade-offs between these two performance indexes. In the proposed numeric evaluation, type-2 fuzzy models are evaluated against their associated type-1 counterparts (the type-2 associated type-1 models sharing similar structure and the same development method). Three architectures of fuzzy models are involved in the comparative studies presented here: (1) fuzzy clustering method-based Takagi-Sugeno (TS) fuzzy models (Fuzzy C-Means based type-1, Fuzzy C-Means based interval type-2); (2) static TS-based fuzzy models (static type-1, A2C0, A2C1, EKFT2 and their associated type-1 models) and (3) evolving TS fuzzy models (SEIT2 and its associated type-1 counterpart, SCIT2 and its associated type-1 model). The experiments are carried out by involving 15 publicly available datasets. The accuracy of these two types of fuzzy models is assessed vis-a-vis their development time. Testing is involved to evaluate whether there are statistically significant differences between the performance of the type-2 and type-1 fuzzy models.

A comparative experimental evaluation of the performance of additive compounds for inhibition of asphaltene precipitation from crude oil

ABSTRACT In this work, the effects of four different chemical inhibitors, namely a polymeric surfactant, synthesized γ-Al2O3/NiO nanoparticles, epoxy resin, and canola oil to inhibit asphaltene precipitation in three different crude oils collected from various oil fields located in southern Iran. A high-pressure solid detection apparatus was employed to measure the onset point of asphaltene precipitation in crude oils with API ranging between 35 and 38 and various characteristics in the presence of the inhibitors in a wide range of concentrations ranging 0–20 wt. % at a high pressure of 2,000 psi and ambient temperature. The elemental composition of resin and asphaltene fractions in the crude oils was identified using a LEC elemental analyzer. The results showed that all fractions of precipitated asphaltenes were composed of low ratios of H (hydrogen)/C (carbon), which were an indication of large instability. Moreover, the screening experiments showed that the polymeric surfactant inhibitor with a base-nature was more efficacious with most oil samples due to the presence of high content (73%) of resin in this type of inhibitor. Besides, they can be used as a well-candidate for other oils not assessed in this work due to their high polarity and also compatibility with the structure of studied asphaltenes. It was found that the polymeric surfactant γ-Al2O3/NiO nanoparticles had the highest inhibition performance in comparison with the epoxy resin and canola oil.